Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MedUniSeg: 2D and 3D Medical Image Segmentation via a Prompt-driven Universal Model
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.05905.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:02:24.992763Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T04:32:24.304511Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation bc577a8a-68af-4a0f-8ded-b64e80d0da06 · inbound
Prompt Mechanisms in Medical Imaging: A Comprehensive Survey cites this paper.
Prompt Mechanisms in Medical Imaging: A Comprehensive Survey MedUniSeg: 2D and 3D Medical Image Segmentation via a Prompt-driven Universal Model
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:02:24.992763Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d0e99ef-1b46-4c9d-a534-138e6768d672 · inbound
DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation cites this paper.
DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation MedUniSeg: 2D and 3D Medical Image Segmentation via a Prompt-driven Universal Model
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:10:57.286283Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a6697f8d-391e-4946-adaf-6fe9fbf37b9e · inbound
MedSeqFT: Sequential Fine-tuning Foundation Models for 3D Medical Image Segmentation cites this paper.
MedSeqFT: Sequential Fine-tuning Foundation Models for 3D Medical Image Segmentation MedUniSeg: 2D and 3D Medical Image Segmentation via a Prompt-driven Universal Model
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T04:32:24.309767Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.